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jajulwar, kapil, Ghodmare, sugesh, Jattewar, Poonam. (1404). Design of AI based Autonomous Navigation System Using Swarm Intelligence Techniques for Agriculture Application. نشریه مهندسی عمران امیرکبیر, (), -. doi: 10.22060/ajme.2025.24228.6186
kapil kamalakar jajulwar; sugesh Ghodmare; Poonam subhash Jattewar. "Design of AI based Autonomous Navigation System Using Swarm Intelligence Techniques for Agriculture Application". نشریه مهندسی عمران امیرکبیر, , , 1404, -. doi: 10.22060/ajme.2025.24228.6186
jajulwar, kapil, Ghodmare, sugesh, Jattewar, Poonam. (1404). 'Design of AI based Autonomous Navigation System Using Swarm Intelligence Techniques for Agriculture Application', نشریه مهندسی عمران امیرکبیر, (), pp. -. doi: 10.22060/ajme.2025.24228.6186
jajulwar, kapil, Ghodmare, sugesh, Jattewar, Poonam. Design of AI based Autonomous Navigation System Using Swarm Intelligence Techniques for Agriculture Application. نشریه مهندسی عمران امیرکبیر, 1404; (): -. doi: 10.22060/ajme.2025.24228.6186

Design of AI based Autonomous Navigation System Using Swarm Intelligence Techniques for Agriculture Application

AUT Journal of Mechanical Engineering
مقالات آماده انتشار، پذیرفته شده، انتشار آنلاین از تاریخ 03 آذر 1404
نوع مقاله: Research Article
شناسه دیجیتال (DOI): 10.22060/ajme.2025.24228.6186
نویسندگان
kapil kamalakar jajulwar* 1؛ sugesh Ghodmare2؛ Poonam subhash Jattewar3
1Assistant professor, Department of Electronics & Telecommunication . G H Raisoni College of Engineering Nagpur (NDIA)
2Department of Civil Engineering G H Raisoni College of engineering Nagpur
3Department of Electronics & telecommunication Engineering KDK College of Engineering Nagpur (India)
چکیده
Agriculture in developing regions still depends heavily on manual labor and low-precision tools, resulting in low efficiency and high resource usage. This paper presents the design of an AI-based Autonomous Navigation System using Swarm Intelligence (SI) for smart farming. The proposed system integrates Particle Swarm Optimization (PSO) and Ant Colony Optimization (ACO) algorithms with Simultaneous Localization and Mapping (SLAM) to achieve cooperative navigation among multiple agricultural robots. The hybrid AI–SI framework enables dynamic obstacle avoidance, decentralized decision-making, and adaptive path planning under uncertain field conditions. Simulation and semi-field experiments demonstrate that the system improves navigation accuracy by 35 %, obstacle-avoidance success by 22 %, and reduces energy consumption by 15 % compared with conventional techniques. The study provides a novel contribution by fusing AI reasoning with swarm-based collaboration for reliable, energy-efficient, and scalable autonomous farming.Agricultural automation faces challenges such as unpredictable terrain, labor shortages, and inefficient resource utilization. This research introduces an AI-based Autonomous Navigation System using Swarm Intelligence (SI) designed for agricultural applications. The proposed system integrates Particle Swarm Optimization (PSO) and Ant Colony Optimization (ACO) with Simultaneous Localization and Mapping (SLAM) to achieve real-time cooperative path planning, obstacle avoidance, and field coverage. The novelty of this work lies in combining AI reasoning and swarm coordination to o
کلیدواژه‌ها
Swarm Intelligence &؛ SLAM Technology ,Agricultural robots , optimize agricultural operation, agricultural industry , agricultural sustainability
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